The present disclosure relates generally to semiconductor device manufacturing, and more particularly to a method for integrating real-time process tool data, process tool fault detection and the in-line product metrology data for improved process control and capabilities.
The manufacture of semiconductor integrated circuits (ICs) and devices require the use of many production process steps to define and create the circuit components and circuit layouts of the product device. The numerous process steps require the use of many tools, both production and support related. Semiconductor factories remain competitive by continuously seeking new methods and practices for improving process yields, product yields, quality, reliability and lower production costs. To help accomplish these, tremendous amounts of effort have been focused upon monitoring aspects of the tools' hardware and processes to ensure and maintain stability, repeatability and yields. In-line product measurements are performed as additional checks to verify these efforts. Such monitoring and check techniques are common methods for controlling process and tool stability and capabilities.
Many conventional production tool monitoring methodologies include tool fault detection and classification (FDC) systems to monitor for and catch drifting and/or shifted tools which will cause processes to go out of control. Metrology tools are used for measuring certain details of the product immediately in-line after undergoing processing operations through specified production tools. The methodologies may also include advance process control (APC) systems by which the in-line measured product metrology is tracked for trend performance. The APC systems will often incorporate algorithms by which pre-determined responses are triggered based upon programmed data trend and excursion patterns. Such responses may involve the re-adjustment of the process tools' processing parameters such that the in-line product measured parameter is tweaked or re-centered back into a desirable performance trend or range.
FIG. 1 illustrates a process and tool control flow diagram 100 for a conventional semiconductor processing operation. The process starts with a given product having been processed through a production tool 102. A metrology tool 104 is then used to measure a certain product performance feature associated with the processing through the production tool 102. The measured metrology data is then sent to a metrology database 106 for storage and assimilation. The APC system controller 108 then judges the stored metrology data 106 to determine if undesired process, tool performance data trends and/or excursion patterns have developed. Run-based algorithms incorporated into the APC 108 may then be used to calculate and feed back processing parameter adjustments 110 to the process tool 102 in an attempt to re-center the measured product metrology index 106 that is produced by the drifted or shifted process tool 102.
A tool fault detection, classification system (FDC) 112 may be used to independently monitor and classify specific errors and faults for the process tool 102. The FDC system 112 monitors and classifies tool faults 114 by checking the operational and processing conditions for conformance to pre-defined limits. When certain faults 114 are detected and classified, the FDC system 112 will typically react with pre-determined responses to raise alerts and/or tool, process shutdowns as required and defined by the manufacturing operations.
The described conventional control methodology is somewhat effective for maintaining process and tool control. However, there are inherent inefficiencies to the system. The methodology is not real-time controlled as there are time lags from the time the production material is processed through the tools and to the time the APC controller reviews the in-line product data and prescribes possible tool process parameter adjustments. This lag time may allow for additional, undesired production material to be processed through a drifting or shifted tool. The APC system depends largely upon the metrology tool data. If the metrology system and/or measurements are defective themselves, the APC may be led to wrong, incorrect responses. The overall methodology responds to symptoms that are manifested upon a measured aspect of the product, rather than responding to the tool's root cause factor of the process tool's shift and/or drift. Process parameters adjustments made by the APC system may not necessarily fix and resolve the root cause issue with the process tool. There is not a direct relational correlation established between the tool root cause drift/shift factors to the process resultant control and symptoms. The FDC is an independent system that does not have any direct influence upon the adjusted process parameters as prescribed by the APC. Without such direct ties, the process tool control methodology may at times become inefficient causing multiple parameter adjustments and metrology check iteration loops as the APC utilizes indirect symptomatic product data to adjust process parameters in the attempt to fix and correct a tool drift/shift root cause issue.
What are needed are improved methods that reduce the response times to react to the product data, thus reducing the incidences of flawed product material.